Improvement in Power Control of Doubly Fed Induction Generator Using an Interval Type-2 Fuzzy Logic Controller

Abstract

This article presents two advanced fuzzy logic control algorithms—Type 1 (T1-FLC) and Interval Type 2 (IT2-FLC)—applied to regulate a doubly fed induction generator (DFIG)  for a wind energy conversion system (WECS). These nonlinear control methodologies are effective in addressing model uncertainties. Although T1-FLCs perform adequately in many scientific and engineering applications, their efficacy diminishes under conditions of significant uncertainty arising from parameter variations, abrupt speed changes, or external disturbances. Conversely, IT2-FLCs constitute a more recent class of intelligent controllers explicitly designed to enhance robustness against such uncertainties and unreliable information. The proposed control strategy incorporates a dual-loop structure, featuring an inner loop for rotor current regulation and an outer loop for stator power control. Simulation results under diverse speed and parameter variations confirm that IT2-FLC exhibits superior robustness, faster response times, reduced overshoot, and achieves a 26.22% and 77.82% reduction in current total harmonic distortion (THD) compared to the T1-FLC approach.